Presentation information

Organized Session

Organized Session » OS-18

[2D6-OS-18c] OS-18 (3)

Wed. Jun 10, 2020 5:50 PM - 7:10 PM Room D (jsai2020online-4)

岩澤 有祐(東京大学)、鈴木 雅大(東京大学)、山川 宏(東京大学/全脳アーキテクチャ・イニシアティブ)、松尾 豊(東京大学)

6:30 PM - 6:50 PM

[2D6-OS-18c-03] Language Model-based Context Augmentation for World Knowledge Bases

〇Rafal Rzepka1,2, Sho Takishita1,2, Kenji Araki1 (1. Hokkaido University, 2. RIKEN AIP)

Keywords:common sense, language models, knowledge acquisition

Lack of background knowledge about the everyday world is an obstacle on the way to simulate usual situations and their changes. In this paper we present a simple idea for extending common sense knowledge bases for Japanese language by using a language model. We investigate several semantic categories for which specific knowledge is collected with mask prediction functionality of BERT and the polarity calculation with both next sentence prediction and masking with lexicons. We describe the experimental results and analyze the discrepancies between human evaluators and utilized sentiment analyzer.

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